1. Field of the Invention
Embodiments of the present invention relate generally to digital media and, more specifically, to recommending digital content based on implicit user identification.
2. Description of the Related Art
Digital content distribution systems conventionally include a content server, a content player, and a communications network connecting the content server to the content player. The content server is configured to store digital content files, which can be downloaded from the content server to the content player. Each digital content file corresponds to a specific identifying title, such as “Gone with the Wind,” which is familiar to a user. The digital content file typically includes sequential content data, organized according to playback chronology, and may comprise audio data, video data, or a combination thereof.
The content player is configured to download and play a digital content file, in response to a user request selecting the title for playback. The user is typically presented with a set of recommended titles for selection. Such recommendations are based primarily on previous operations and/or selections performed by the user. However, in a scenario where multiple users interact with the same content player, the recommendations can be inaccurate. For example, if user A performs certain actions within the content player, the next time any user other than user A, such as user B or C, interacts with the same content player, the recommendations may be based on the actions performed by user A. Further, user A may have one set of interests when interacting with the content player alone and a different set of interests when interacting with the content player in a group. In such a scenario, recommendations based primarily on previous operations and/or selections performed by user A can be inapplicable if the determination is not made regarding who is interacting with the content player. Lastly, in a scenario where the same user may be in different moods/interests at different times, the recommendations can be in applicable if the current mood/interest of the user is not determined.
One solution to the above-mentioned inaccuracy is having the users of the content player explicitly identify themselves (or their mood/interest) every time they begin interacting with the content player. However, this explicit identification puts an additional burden on the user when interacting with the content player and, therefore, is not a desirable user experience.
As the foregoing illustrates, what is needed in the art is an approach for recommending digital content to a user based on his/her identity without requiring explicit identification from the user, or any additional inputs about their interests.